U.S. patent number 7,356,100 [Application Number 10/616,875] was granted by the patent office on 2008-04-08 for estimating channel impulse response and equalizer coefficients in uwb communication systems.
This patent grant is currently assigned to Mitsubishi Electric Research Laboratories, Inc.. Invention is credited to Ye Li, Andreas Molisch, Jinyun Zhang.
United States Patent |
7,356,100 |
Molisch , et al. |
April 8, 2008 |
Estimating channel impulse response and equalizer coefficients in
UWB communication systems
Abstract
A method estimates a channel impulse response in an ultra wide
bandwidth (UWB) system. Multiple training sequences modulated at a
chip rate are received. Each training sequence is sampled by
parallel with multiple correlators at sampling rate substantially
slower than the chip rate to obtain a samples over a time interval
of the impulse response at a resolution substantially equal to the
chip rate, and then estimating the channel impulse response from
these samples.
Inventors: |
Molisch; Andreas (Arlington,
MA), Li; Ye (Marietta, GA), Zhang; Jinyun (Cambridge,
MA) |
Assignee: |
Mitsubishi Electric Research
Laboratories, Inc. (Cambridge, MA)
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Family
ID: |
32994434 |
Appl.
No.: |
10/616,875 |
Filed: |
July 10, 2003 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20040185787 A1 |
Sep 23, 2004 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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60451528 |
Mar 3, 2003 |
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Current U.S.
Class: |
375/343; 375/136;
375/229; 375/239; 375/340; 375/349 |
Current CPC
Class: |
H04B
1/71637 (20130101); H04B 1/719 (20130101); H04L
25/0212 (20130101); H04L 25/0226 (20130101); H04L
25/03012 (20130101); H04L 1/203 (20130101); H04B
1/709 (20130101); H04L 2025/03484 (20130101) |
Current International
Class: |
H04L
27/06 (20060101); H04B 1/00 (20060101) |
Field of
Search: |
;375/295,303,324,340,130,329,148,149,343,239,150,138,242,247,147,203,256,355,367 |
References Cited
[Referenced By]
U.S. Patent Documents
Other References
Namgoong "A Channelized DSSS Ultra-Wideband Receiver" IEEE 2001.
cited by examiner .
Won Namgoong "A Channelized DSSS Ultra-Wideband Receiver", IEEE
2001. cited by examiner.
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Primary Examiner: Ghayour; Mohammed
Assistant Examiner: Vlahos; Sophia
Attorney, Agent or Firm: Brinkman; Dirk Mueller; Clifton D.
Vinokur; Gene V.
Parent Case Text
CROSS-REFERENCE TO RELATED APPLICATIONS
A claim of priority is made to U.S. Provisional Patent Application
Ser. No. 60/451,528, filed Mar. 3, 2003, entitled "Channel
Estimation and Equalizer Coefficient Estimation for UWB Radio
Communication Systems."
Claims
We claim:
1. A method for estimating a channel impulse response in an ultra
wide bandwidth (UWB) system comprising the steps of: generating a
training sequence; modulating the training sequence at a chip rate
to produce a modulated training sequence, the modulated training
sequence being comprised of ultra wide bandwith radio pulses;
generating a training signal comprised of a plurality of
repetitions of the modulated training sequence; transmitting and
receiving, via a channel, the training signal; sampling the
received training signal, in parallel, with a set of correlators to
obtain a plurality of samples, in which each correlator samples the
received training signal at a sampling rate substantially slower
than the chip rate, each correlator samples the received training
signal at a different delay for each repetition of the modulated
training sequence in the received training signal, and such that
the plurality of samples spans a time interval corresponding to an
impulse response of the channel at a resolution substantially equal
to the chip rate; and estimating the impulse response of the
channel over the time interval corresponding to the impulse
response of the channel from the plurality of samples.
2. The method of claim 1, in which the training signal comprises m
repetitions of the modulated training sequence, and further
comprising: sampling, in each of n correlators, the training signal
k times per repetition of the modulated training sequence in the
received training signal to produce m.times.n.times.k samples of
the received training signal.
3. The method of claim 1, in which the sampling rate is at least
ten times slower than the chip rate.
4. The method of claim 1, in which the sampling rate is equal to a
symbol rate of the training sequence.
5. The method of claim 1, further comprising: estimating equalizer
coefficients from an equalizer training sequence consisting of
radio pulses.
6. The method of claim 1, further comprising: estimating weights
for the corresponding correlators to acquire most of the available
energy of a data signal received via the channel, in which the data
signal consists of ultra wide bandwith radio pulses.
7. The method of claim 1, in which a first subset of the plurality
of samples are used for a rough estimate of the impulse response of
the channel, and a second subset of the plurality of samples are
used for an accurate estimate of the impulse response of the
channel based on the rough estimate.
8. The method of claim 1, in which the estimate of the impulse
response of the channel is based on a previous estimate of the
impulse response of the channel.
9. The method of claim 2, where k is greater than one.
10. The method of claim 3, in which the chip rate is on the order
of 10 GHz.
11. The method of claim 7, in which the second subset of the
plurality of samples are obtained from training sequences received
after obtaining the first subset of the plurality of samples.
12. The method of claim 2, where k is equal to one.
Description
FIELD OF THE INVENTION
The present invention relates generally to radio communication
systems, and more particularly to channel and equalization
estimation in an ultra wide bandwidth communications systems.
BACKGROUND OF THE INVENTION
With the release of the "First Report and Order," Feb. 14, 2002, by
the Federal Communications Commission (FCC), interest in ultra wide
bandwidth (UWB) communication systems has increased. The IEEE
802.15 standards organization, which is responsible for Personal
Area Networks, has established a task group, TG3a, to standardize a
high-data-rate physical layer based on UWB.
Ultra wide bandwidth (UWB) communication systems transmit and
receive extremely short electromagnetic energy impulses, therefore
the terms "UWB" and "impulse radio" are used synonymously herein.
Because the bandwidth of the pulses is much wider than the
bandwidth of the payload signal, UWB is a form of spread-spectrum
communication. Each pulse can cover anywhere from 500 MHz to
several GHz of the radio spectrum.
Information is transmitted by modulating the frequency, timing,
amplitude, polarity, or other aspect of the pulses. UWB systems can
provide very high data rates for short-range wireless
communications. In part, UWB systems are designed to distribute
information in home, office, school, and industrial environments
using high-speed links between computer devices.
However, it is a challenge to realize UWB modulation schemes that
increase data throughput while minimizing errors in dense
multi-path environments. Propagation measurements and channel
modeling studies indicate that many multi-path components (MPCs)
are expected for an UWB radio link. In a dense multi-path
environment, the number of MPCs increases linearly with the
bandwidth.
For example, a system with a 10 GHz bandwidth, operating in an
environment with a maximum excess delay spread of 100 ns requires a
thousand fingers in a rake receiver. Even in a sparse multi-path
environment, like the channels specified by the IEEE 802.15.3a
standard for channel models, up to 80 fingers are required to
collect 80% of the available energy.
In order to collect most of the available energy from MPCs, while
at the same time reducing the number of fingers in the rake
receiver, it is desired to estimate the channel impulse response so
that the correct reference waveforms for convolutions with the
received signal at each rake finger can be determined.
The requirements for channel estimation in the IEEE 802.15.3a
standard for data format are stringent. Data are to be transmitted
in blocks of 8,000 bits. It is also assumed that the channel can
change from block to block. Each block of data lasts only 0.1 ms.
The typical speed of movement in an indoor environment is about 1
meter per second, so for a 10 GHz upper frequency limit, the
maximum Doppler frequency is 30 Hz. Thus, the channel stays
stationary for only 30 ms.
The impulse responses can last up to 200 ns, as can be seen in the
Final Report and Order. Because sampling has to be done at a rate
of about 10 G samples per second, this means that 2000 samples of
the channel impulse response have to be evaluated. If data are
transmitted in a constant stream, then is should be possible to
exploit the correlation between channel realizations.
In the prior art, the channel impulse response and equalizer
coefficient are usually estimated from a single pseudo-noise (PN)
training sequence. However, other users and out-of-band interferers
might be transmitting while the single training sequence is
transmitted. Therefore, there is a need to suppress co-channel
interferers. This can be done by spreading the training
sequence.
A brute-force approach samples and A/D converts the measured
impulse response at a speed of 10 G samples per second. In
principle, the channel sounding requires only two microseconds,
i.e., the length of the impulse response times a factor of 10 for
the interference suppression, which is 200 symbol durations. This
is much shorter than the duration of the data block, and thus is
not a significant overhead. However, A/D converters that can
process 10,000,000,000 samples per second are prohibitively
expensive.
During the estimation period, while the single training sequence is
transmitted, it is necessary to sample the received signal at a
chip rate to find the delays and amplitudes of the received
multi-path components. Because the number of MPCs is not yet known
at this time, each possible resolvable delay, i.e., each chip
period, must be estimated. For a 10 GHz system, that again means
sampling and A/D converting at 10 G samples/s, which is
prohibitively expensive.
Therefore, there is a need for method and system that can estimate
the channel impulse response and equalizer coefficient at a lower
cost without degrading performance.
SUMMARY OF THE INVENTION
It is an object of the invention to provide a low cost channel
estimator that can estimate the channel impulse response and
equalizer coefficients in an ultra wide bandwidth (UWB)
communications system.
According to the present invention, multiple training sequences are
transmitted. Each training sequence includes, for example, fifteen
symbols, and the training sequence is repeated, for example,
fourteen times to suppress interference. There is a guard interval
between two consecutive training sequences to avoid inter-sequence
interference. Each symbol is `spread` over the spectrum by a
predetermined sequence of chips at a chip rate.
After front-end processing, the UWB signal of the training
sequences is passed to a rake-like receiver structure with a small
number of parallel correlators (fingers), for example, three, for
channel impulse response estimation.
The fingers sample each received training sequence, in parallel,
with different time offset to produce samples. The samples
substantially span the entire time interval of the impulse
response. If the training sequence is repeated, then the samples
have a fine resolution, and the channel impulse response can be
estimated from the transmitted signal and the samples.
After the channel has been estimated, the weights for the rake
receiver used for the data reception are determined. Finally,
equalizer coefficients are estimated by minimizing the error
between equalized outputs and the equalizer training sequence.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a detailed block diagram of a receiver with channel
impulse response and equalizer coefficients estimation according to
the invention;
FIG. 2 is a timing diagram of multiple training sequences according
to the invention;
FIG. 3 is a flow diagram of a method for the estimating according
to the invention;
FIG. 4 is a graph comparing results obtained by the estimating
according to the invention;
FIG. 5A is a graph showing bit error rates;
FIG. 5B is a graph showing normalized mean-square errors;
FIG. 6 is a block diagram of a UWB system according to the
invention; and
FIG. 7 is a block diagram of a UWB receiver according to the
invention; and
FIG. 8 is timing diagram of rough and accurate estimates of an
impulse response according to the invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
System Structure and Operation
FIG. 6 shows a UWB system according to the invention. The system
includes a transmitter 601 and a rake-like receiver 100 connected
via a wireless channel 603. Both the transmitter and the receiver
include a clock (CLCK) 604. The clocks are synchronized 605 to each
other. The details of how this is achieved can vary, see, e.g.,
Meyr et al., Synchronization, Channel Estimation, and Signal
Processing, Volume 2, Digital Communication Receivers, Wiley, 1997.
The transmitter sends m training sequences 200 as described in
detail below. The pulses of the training sequences are modulated at
a chip rate.
As shown in FIG. 7, each of the m training sequences 200 is passed,
in parallel, through multiple correlators 701 (rake fingers) of the
receiver 100. Parallel "sample and hold" circuits 702 sample each
received training circuits at multiple delay points with fixed
offsets to obtain at least one (k=1) sample for each training
sequence. It should be noted that each of the n fingers can also
obtain serially more samples (k>1). Thus, the total number of
samples can be expressed as (m.times.n.times.k). The idea is that
these samples span a time interval corresponding to the impulse
response at a resolution that is substantially equal to the chip
rate.
However, the actual sampling rate according to the invention is at
a substantially lower rate then the prior art sampling at the chip
rate (on the order of 10 GHz) because the sampling extends over a
longer period of time of the multiple training sequences. In fact,
the sampling rate can be at the symbol rate (110 MHz in an
802.15.3a system). It should be understood that the sampling can
also be at other low sampling rates. Thus, low cost components can
be used for the receiver according to the invention, and the
primary object of the invention is achieved.
After the sampling, the analog signal is AID converted 703 to a
digital signal. The (m.times.n.times.k) digital signals from the
fingers are further processed 705 to determine the channel impulse
response.
In a second, optional, step, the estimate of the channel impulse
response is then used to determine the weights of the rake
receiver. For the basic prior art method see Molisch, Wideband
Wireless Digital Communications, Prentice-Hall, 2001.
The rake coefficients are then used to weigh the output of the
correlators 701 so that most of the available energy of the signal
can be acquired. Thus, the invention estimates an "effective
channel" from the antenna of the transmitter to the output of the
summation device. Optionally, additional training sequences can be
sampled at the symbol rate to provide an estimate of the channel
impulse response of the effective channel, which, in turn, is the
basis for the determination of the coefficients of an equalizer.
The low rate samples are thus used to determine a full-resolution
impulse response of the channel, and equalizer coefficients for the
receiver. All of this is now described in greater detail.
Signaling Format
In the transmitter, symbols are generated at a symbol rate
1/T.sub.s. Transmitted pulses p corresponding the symbols are in
the form of a Gaussian function
.function..times.e.times..sigma. ##EQU00001## whose Fourier
transform is
.function..omega..times.e.sigma..times..omega. ##EQU00002## In this
example, the variance .sigma..sup.2 is determined by
.intg..times..pi..times..times..times..pi..times..times..times..function.-
.omega..times..times.d.omega..intg..infin..infin..times..function..omega..-
times..times.d.omega. ##EQU00003## where f is the frequency. From
p(t), the spreading waveform can be obtained by
.function..times..times..times..function. ##EQU00004## where
1/T.sub.c is the chip rate, which is substantially faster than the
symbol rate. An example spreading sequence is
{s.sub.k}={-1-1-1+1+1-1+1+1}. If the symbol sequence to be
transmitted is {b.sub.k}, then the transmitted signal can be
expressed as
.function..infin..infin..times..times..times..function.
##EQU00005##
Detailed Receiver Structure
FIG. 1 shows the rake-like receiver 100 according to the invention
in greater detail. The receiver includes a conventional front-end
101 and three fingers 110 to acquire most of the available energy
of a received signal 102. Each finger 110 includes a multiplier and
low-pass filter 111, a programmable training pulse generator 112.
These comprise the correlators 701 and sample and hold circuits 702
of FIG. 7.
Adjustable weight blocks 113 operate on digital signals 114. For
clarity the details of the sampling and A/D circuits of Figure are
not shown here. The digital signal is functionally related to a
product of the output of the front end and the output of the
programmable pulse generator.
The receiver also includes a timing controller 140 for the
programmable training pulse generators 112. A channel estimator 150
provides input for the timing controller and an estimate 151 of the
channel impulse response, which is used by the timing controller
140. A weight controller 155 adjusts the weights of the weight
blocks 113 of each finger according to the estimated channel
impulse response. An equalizer (EQ) training sequence generator 160
generates an equalizer training sequence 161 for an equalizer
estimator 170 that produces coefficients 171 for a three-tap
equalizer 130. The receiver produces output 131 is also fed back to
the equalizer estimator.
After summing 120, a combined output 121 can be expressed as
.function..times..times..times..gamma..times..intg..function..tau..times-
..DELTA..times..function..tau..times.d.tau..times..times..times..gamma..ti-
mes..function..times..DELTA. ##EQU00006## where
r(t)=.intg.s(t+.tau.)w*(.tau.)d.tau., .lamda..sub.k is the impulse
response of the channel at n.sub.0.DELTA., where .DELTA. is a
minimum timing offset between two fingers.
To acquire as most of the available energy, we select {n.sub.1,
n.sub.2, n.sub.3} such that {.gamma..sub.n.sub.1,
.gamma..sub.n.sub.2, .gamma..sub.n.sub.3} correspond to the three
taps with largest energy magnitudes.
The three-tap linear equalizer 130 is used to mitigate residual
inter-symbol-interference (ISI). If the coefficients of the
equalizer are {c.sub.-1, c.sub.0, c.sub.1}, then the equalizer
output 131 is
.times..times..times..function. ##EQU00007##
To optimize performance, the equalizer coefficients 171 are
selected to minimize a mean square-error of its output, that is
MSE=E|{tilde over (b)}.sub.n-b.sub.n|.sup.2.
Channel Estimation and Equalizer Coefficient Estimation
Training Sequences
FIG. 2 shows the structure of the m pseudo-noise (PN) training
sequences 200 according to the invention. Each of the multiple
training sequences uses fifteen symbols 201-215. Each symbol is 75
nsec in duration, followed by a guard interval of 125 usec, for a
total of 1250 nsec. If the sequence is repeated fourteen times
211-224, then the channel coefficients can be estimated in 17.5
.mu.sec 250, followed by 2.5 .mu.sec 270 for equalizer coefficients
estimation, for a total of 20 .mu.sec. The sequences can be the
same or different.
Channel Impulse Response Estimation
Each training sequences are sampled, in parallel, at a symbol rate
(1/T.sub.s). During each symbol period, we observe at least n
samples, e.g., three if there are three fingers. Because we need to
estimate the entire impulse response at a resolution of the chip
rate, we need forty samples during the symbol interval. Therefore,
we repeat the training sequence fourteen (40/3) times. The timing
offset of each finger can be adjusted by the controller 140 so that
the output of each finger is as indicated in Table A below.
TABLE-US-00001 TABLE A Sequence Output of the Output of the Output
of the No. 1st finger 2.sup.nd finger 3.sup.rd finger 1
r(40n.DELTA.) r(40n.DELTA. + 14.DELTA.) r(40n.DELTA. + 28.DELTA.) 2
r(40n.DELTA. + .DELTA.) r(40n.DELTA. + 15.DELTA.) r(40n.DELTA. +
29.DELTA.) 3 r(40n.DELTA. + 2.DELTA.) r(40n.DELTA. + 16.DELTA.)
r(40n.DELTA. + 30.DELTA.) 4 r(40n.DELTA. + 3.DELTA.) r(40n.DELTA. +
17.DELTA.) r(40n.DELTA. + 31.DELTA.) 5 r(40n.DELTA. + 4.DELTA.)
r(40n.DELTA. + 18.DELTA.) r(40n.DELTA. + 32.DELTA.) 6 r(40n.DELTA.
+ 5.DELTA.) r(40n.DELTA. + 19.DELTA.) r(40n.DELTA. + 33.DELTA.) 7
r(40n.DELTA. + 6.DELTA.) r(40n.DELTA. + 20.DELTA.) r(40n.DELTA. +
34.DELTA.) 8 r(40n.DELTA. + 7.DELTA.) r(40n.DELTA. + 21.DELTA.)
r(40n.DELTA. + 35.DELTA.) 9 r(40n.DELTA. + 8.DELTA.) r(40n.DELTA. +
22.DELTA.) r(40n.DELTA. + 36.DELTA.) 10 r(40n.DELTA. + 9.DELTA.)
r(40n.DELTA. + 23.DELTA.) r(40n.DELTA. + 37.DELTA.) 11 r(40n.DELTA.
+ 10.DELTA.) r(40n.DELTA. + 24.DELTA.) r(40n.DELTA. + 38.DELTA.) 12
r(40n.DELTA. + 11.DELTA.) r(40n.DELTA. + 25.DELTA.) r(40n.DELTA. +
39.DELTA.) 13 r(40n.DELTA. + 12.DELTA.) r(40n.DELTA. + 26.DELTA.)
14 r(40n.DELTA. + 13.DELTA.) r(40n.DELTA. + 27.DELTA.)
If the training sequence bt.sub.k 's for k=0, 1, . . . , 14, then
the training sequence can be expressed as
.function..times..times..times..function. ##EQU00008## and the
channel output is xt(t)=h(t)*st(t)+nt), where h(t) is the channel's
impulse response and n(t) is additive white Gaussian noise.
The .DELTA.-sampled output of each correlator is
r(n.DELTA.)=.intg.xt(n.DELTA.+.tau.)st*(.tau.)d.tau.. If the
training sequence st(t) is white, then the channel parameters can
be estimated by
.function..times..times..DELTA..apprxeq..function..times..times..DELTA..f-
unction. ##EQU00009## However, st(t) is not perfectly white.
Therefore, we modify the above estimation by the following discrete
Fourier transform (DFT) steps: 1) Find the DFT of h(n.DELTA.),
H.sub.k=DFT{h(n.DELTA.)}. 2) Find the DFT of st(t),
St.sub.k=DFT{st(n.DELTA.)}. 3) Modify the DFT of h(n.DELTA.) by
i.
.rho. ##EQU00010## 4) Find the modified channel estimation by
h(n.DELTA.)=I-DFT{H.sub.k}.
Improved Channel Estimation
Because the channel impulse response is correlated for the
sub-channels, the estimation of the channel impulse response can be
improved, as shown in FIG. 3. For the first few, e.g., two,
training sequences, set the timing offsets of the rake fingers of
different sub-channels for rough channel estimation 310. This
locates the portions of the impulse response that contain most of
the available energy. Identify 320 the largest (six) taps according
to the rough channel estimation. That is, set the offset timing so
as to only sample near the rough estimates, instead of over the
entire span of the impulse response. Then, estimate 340 the impulse
response more accurately using another four training periods or
5000 nsec, and identify 350 the largest three taps from the six
taps for the rake receiver and channel equalization.
As shown in FIG. 8, the rough estimates 801 for an impulse response
800, are used as a basis for the accurate estimates 802. Obviously,
the rough to accurate refinement can be done in any number of
steps.
It should be noted that more then one sample can be acquired
concurrently by each rake finger for each training sequence. For
example, if k (two or more) samples are taken at different time
offsets, for each sequence, then the number of required sequences
can reduced.
This simplified estimator only needs six training sequences instead
of fourteen, which only requires 7500 nsec. Together with another
2500 nsec for equalizer coefficient estimation, the overall
simplified estimation takes is only 10 usec, which is half the time
required to estimate the channel from fourteen sequences.
It should also be noted, that the channel is re-estimated for each
transmitted block. If the channel is slow-varying, a previous
estimate can be used as a starting point for a next estimate to
further reduce the required time.
Equalization Coefficient Estimation
After the impulse response is estimated, the rake receiver can be
used to acquire most of the available energy of the received
signal, and to mitigate the residual ISI. Therefore, after
processing the training sequences for channel estimation, another
training sequence is sent for equalizer coefficient estimation.
If the output of the rake receiver is x[n] when the training
sequence is ck.sub.k., then the equalizer coefficients can be
estimated by minimizing
.times..times..times..times..function. ##EQU00011##
Consequently
.times..times.>.times.>.times..times..times.>.times.
##EQU00012## where
>.function..function..function. ##EQU00013##
FIG. 4 shows results for the channel estimation according to the
invention. When the SNR is below 0 dB, the normalized MSE (NMSE) of
channel estimation decreases with an increase of the SNR. However,
when SNR is above 0 dB, the NMSE has a floor, which is because
training signal is not exciting enough.
The modified approach can significantly improve estimation
performance. It can improve NMSE of overall channel estimation
(whole) by 2 dB and NMSE of the three greatest taps (3-GT) by 2.6
dB.
For the three-tap equalizer output according to the invention, FIG.
5A shows the bit error rate (BER), and FIG. 5A shows the normalized
NMSEe. For a 1% BER, the required SNR is about -2.5 dB.
Although the invention has been described by way of examples of
preferred embodiments, it is to be understood that various other
adaptations and modifications can be made within the spirit and
scope of the invention. Therefore, it is the object of the appended
claims to cover all such variations and modifications as come
within the true spirit and scope of the invention.
* * * * *